An Empirical Study of Mobile Ad Targeting
This addresses the lack of empirical data on mobile ad targeting for advertisers and researchers, though it is incremental as it applies existing statistical methods to a new domain.
The study tackled the problem of understanding mobile ad targeting by analyzing over 225,000 ads on simulated devices, finding that nearly all ads use application- and time-based targeting, with location-based targeting in 43% and user-based targeting in 39% of ads.
Advertising, long the financial mainstay of the web ecosystem, has become nearly ubiquitous in the world of mobile apps. While ad targeting on the web is fairly well understood, mobile ad targeting is much less studied. In this paper, we use empirical methods to collect a database of over 225,000 ads on 32 simulated devices hosting one of three distinct user profiles. We then analyze how the ads are targeted by correlating ads to potential targeting profiles using Bayes' rule and Pearson's chi squared test. This enables us to measure the prevalence of different forms of targeting. We find that nearly all ads show the effects of application- and time-based targeting, while we are able to identify location-based targeting in 43% of the ads and user-based targeting in 39%.